Lecture 4: Data Modeling Process Modeling

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Lecture 4Data ModelingProcess Modeling
MIS 210 Information Systems I
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Data Models
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Entity-Relationship Diagrams

• Data-oriented approach
• uses the data and the relationships among data to
  model requirements
• purpose is to show the data used in the system
• good for modeling data stores from a DFD
• A representation of organizational data.
• Shows the rules about the meanings and
  interrelationships among the data.

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E-R Diagrams

• Defined
• A graphical representation of an E-R model.
• E-R model
• a detailed, logical representation of the
  entities, associations, and data elements for an
  organization or business area.

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E-R Symbols
Entity
Attribute
Relationship
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Terminology

• Entity
• a thing in the real world
• has an independent existence
• Attribute(s)
• One specific piece of information about a thing
• a property of the entity
• has a value (or value set or domain)
• Cardinality
• the number of instances of an entity that are
  associated with another entity
• a single occurrence of an entity

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Data Entities

• An Entity is a thing the users need to know (i.e,
  record) something about.

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Types of Things
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Types of Attributes

• Identifier (primary key / key attribute)
• An attribute (or attributes) selected as the
  unique, identifying characteristic for an entity.
• Foreign Key
• An attribute (or attributes) in one database
  table that is the primary key in another database
  table

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Attributes and Their Values

• All videos/DVDs have the following attributes
• Product ID number
• Product Name
• Product Description
• Category ID
• Supplier ID
• Serial Number

• Each video/DVD has a value for each attribute
• 1
• Woodstock
• Concert
• Other
• WRNRBR
• DVD19925C1

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Relationships

• Relationship
• Naturally occurring association among specific
  things
• Occur in two directions
• Cardinality/multiplicity

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Relationships

• Degree of Relationship
• number of entities that participate in that
  relationship
• Unary (recursive)
• degree one
• A relationship between instances of one entity.
• Binary
• degree two
• A relationship between instances of two entities
• Ternary
• A relationship between instances of three
  entities

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Cardinality of Relationships
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Relationships and Cardinality
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Trucking.One Approach
Truck ID Volume Weight
makes
m
1
Truck
Trips
1
1
m
delivers to
Retail Stores
carries
m
Shipment Number Shipment Volume Weight Destinatio
n
stored at
m
m
Warehouses
Shipment
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Trucking.Another Approach
Truck ID Volume Weight
makes
m
1
Truck
Trips
1
1
m
delivers to
Retail Stores
carries
m
Shipment Number Shipment Volume Weight Destination
stored at
m
m
Warehouses
Shipment
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Data Dictionary
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Data Dictionary Defined

• the data dictionary collects and coordinates
  specific data terms, and it confirms what each
  term means to different people in the
  organization.
• Kendall Kendall

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Data Dictionary(aka, Project Repository)

• Repository for all primitive-level data
  structures and data elements within a system.
• Use information from DFDs or ERDs to create the
  DD
• DD details each of the data items, data flows,
  processes, etc. in a system
• For example DD entry for data items would show
  characteristics such as size, type, description,
  ranges, etc.

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Process Models
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Process Modeling

• Focus on the internal structure and processes in
  the DFD
• Most popular models
• Structured English
• Decision Tables
• Decision Trees

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Structured English

• Form of English used to specify the processes in
  a DFD
• Makes use of nouns and action verbs
• Similar to pseudocode

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Structured English ExampleEnd of Month Processing

• DO FOR EACH INVENTORY ITEM
• COUNT STOCK IN STOCK ROOM
• ENTER COUNT ON INVENTORY SHEET
• END DO

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Decision Tables

• Lays out the logic of complex problems where
  there are multiple actions based on multiple
  decisions.
• Four components
• conditions
• decision rules
• actions
• action entries

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Decision Tables

• The total possible number of decision rules
  represents the total possible combinations, or
  permutations, of the condition values
• For example, for yes or no values
• number of decision rules 2n
• For three conditions with yes or no values
• number of decision rules 2n 23 8

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Decision Tables

• For a range of values
• example, age 118 to 20, 221-30, 331-40,
  441-50, 550 or over
• five (5) values for this condition
• What if there are a combination of different
  values
• yes or no values
• five values
• total possible values 2 x 510

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Decision Trees

• A graphical representation of a decision
  structure.
• Difficult to use for a complex situation.